EP2979406B1 - Termingebundene inhaltslieferung - Google Patents

Termingebundene inhaltslieferung Download PDF

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Publication number
EP2979406B1
EP2979406B1 EP14710940.9A EP14710940A EP2979406B1 EP 2979406 B1 EP2979406 B1 EP 2979406B1 EP 14710940 A EP14710940 A EP 14710940A EP 2979406 B1 EP2979406 B1 EP 2979406B1
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European Patent Office
Prior art keywords
rate
qoe
network
packet
segment
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English (en)
French (fr)
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EP2979406A1 (de
Inventor
Stephen Clifford Appleby
Rory Stewart Turnbull
Michael Eilling NILSSON
Ian Barry Crabtree
Brahim ALLAN
Timothy Sean Stevens
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British Telecommunications PLC
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British Telecommunications PLC
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/25—Flow control; Congestion control with rate being modified by the source upon detecting a change of network conditions
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0823—Errors, e.g. transmission errors
    • H04L43/0829—Packet loss
    • H04L43/0835—One way packet loss
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/12—Avoiding congestion; Recovering from congestion
    • H04L47/127—Avoiding congestion; Recovering from congestion by using congestion prediction
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/28—Flow control; Congestion control in relation to timing considerations

Definitions

  • This invention relates to a method and apparatus for controlling the delivery of content over a shared network.
  • CDNs Content Delivery Networks
  • QoS Quality of Service
  • network QoS is rarely used. It is complex to integrate with services, as they need to be authenticated by the network to ensure that are allowed to prioritise their traffic. More complex systems may require sessions to be set up to reserve capacity. Accounting and billing is also more complex.
  • Each network operator will deploy their own QoS system, and so a national or international service provider will have to go to great expense to integrate many different operators' QoS systems and have an independent commercial relationship with each. For these reasons, QoS is rarely used for services other than those provided by the network operator itself. Even then, it is questionable as to whether it is cost-effective.
  • a method of managing content delivery between a server and a client over a network wherein the content comprises a plurality of segments, and each segment having an associated delivery deadline, said method comprising:
  • the packet dispatch rate may be increased for the next segment. Conversely, if the predicted quality of experience is higher than the network quality of experience, then the packet dispatch rate may be decreased for the next segment.
  • the delivery deadlines for the segments are typically provided by the client to the server together with a request for the content from the server.
  • a server for delivering content to client over a network wherein the content comprises a plurality of segments, and each segment having an associated delivery deadline, said server adapted to:
  • Examples of the present invention present a method of controlling content delivery in a network.
  • a global quality of experience measure, QoE max is calculated based on the packet loss rate in the network. As packet loss rate varies as a result of congestion conditions in the network, so will QoE max .
  • a server delivering content over the network will attempt to reach QoE max for the content in its respective session. Those sessions with a quality of experience, QoE, less than QoE max will try and increase its packet dispatch rate, and those with a QoE higher than QoE max will reduce its packet dispatch rate, subject to any delivery deadlines associated with the session. If the delivery deadlines of the sessions can be met without exceeding QoE max , then all sessions will converge on QoE max . Since QoE max is only a function of packet loss rate that all sessions running over the same shared network agree upon, all sessions should converge on the same QoE max .
  • HTTP HyperText Transfer Protocol
  • HTTP Adaptive Streaming standards replace proprietary protocols, such as RTMP, used by Adobe Flash.
  • HTTP implies the use of TCP as the transport protocol.
  • TCP the transport protocol.
  • the rate at which TCP allows data to be sent is determined primarily by two factors:
  • the rate at which a server sends data is given by the lesser of the rates determined by these two constraints.
  • a session might be a file download or the streaming of a video sequence
  • the fact that the packet loss rate in the network sets an upper bound for the send rate is a principle of TCP-friendliness, which is critical in avoiding congestion collapse.
  • Examples of the present invention propose introducing a modification to the way that the transport protocol behaves, so that instead of packet loss rate imposing a cap on the delivery rate as in standard TCP, the packet loss rate is instead used to determine a nominal maximum QoE for the network.
  • This maximum QoE is then used by all servers to control content delivery in a session, so that content is delivered with a QoE that does not exceed this maximum QoE.
  • QoE max the delivery rate of the content takes into consideration the delivery deadline associated with the content. Both these concepts of QoE and delivery deadlines will be explored in more detail below.
  • Proposed is a global function, fixed for all services, which sets QoE max in dependence on the packet loss rate experienced in the network. This function ultimately determines the bandwidth share amongst multiple services sharing the same network, and together with delivery deadline considerations, provides an alternative congestion response mechanism to standard TCP.
  • This function is generated through testing, with the aim of defining QoE max as a function of packet loss rate.
  • a reference service is chosen, then we try to set the QoE max function in a manner that delivers the service at the same bitrate as a normal TCP session.
  • MSS is the maximum segment size and RTT is the round trip time.
  • the packet loss rate is a measure of the fraction of the data that is lost e.g. 10% of packets.
  • One proposed technique to measure packet loss rate is to use a Weighted Moving Average approach, in particular an Exponentially Weighted Moving Average, in which the significance of later measurements decays exponentially with their age. This is described in more detail in the paper " Equation-Based Congestion Control for Unicast Applications", by Sally Floyd et al, August 2000, SIGCOMM 2000 .
  • equation (4) gives a value for the global measure for QoE, QoE max , for a given packet loss rate.
  • Timeliness of content delivery can be extremely important depending on the session type. Streamed media is the most obvious; where each segment of the media must be received before the client buffer empties, and media playout stalls. The playout rate and buffer fullness thus affects the delivery deadline for each segment of the media. Other examples might include pre-loading media off-peak for playback according to a schedule. In such a session, the media should complete downloading prior to playout.
  • FIG. 1 shows a content server 100 in an example of the invention, comprising a CPU 102 operating under the control of the program modules 104, which may be stored in suitable storage such as a hard disk.
  • a data store 106 is also provided, which can store other data, such as video or any other content served by the content server 100.
  • the CPU 102, program modules 104, and data store 106 are interconnected by way of a suitable bus 108.
  • the content server 100 also comprises a network interface card 110, over which data can be transmitted and received by the content server 100.
  • FIG. 2 shows the program modules 104 in more detail.
  • the program modules 104 include a deadline based packet rate calculator 200, a higher rate selector 202, a packet dispatcher 204, a QoE max calculator 208, and a predicted QoE assessor 210.
  • the deadline based packet rate calculator 200 calculates minimum packet dispatch rates for content, or segment of content, based on an associated delivery deadline.
  • the higher rate selector 202 selects the higher of any packet dispatch rates provides.
  • the resulting packet dispatch rate is passed by the higher rate selector 202 to the packet dispatcher 204, which controls dispatch of packets of the content into the network, at the provided packet dispatch rate.
  • the packet dispatcher 204 also measures the packet loss rate experienced in the network, and passes the resulting packet loss rate to the Qoe max calculator 208, which uses the function set out in equation (4) to calculate QoE max based on the packet loss rate.
  • the predicted QoE assessor 210 determines the QoE of the present or next segment of content to be transmitted, QoE predicted , and passes this to a differentiator 212, which takes the difference between the input QoE predicted and QoE max from the QoE max calculator 208, and outputs a rate that is dependent on both QoE predicted and QoE max to a summer 214.
  • the summer 214 takes the rate and uses it to adjust the packet dispatch rate output by the higher rate selector 202.
  • the summer 214 outputs this summed rate to the higher rate selector 202, which selects the higher of this rate and the rate from deadline based packet rate calculator 200, and outputs it to the packet dispatcher 204 for use on subsequent packets, and so on.
  • FIG. 3 shows a network arrangement 300, comprising content servers 302 and 304.
  • content server 302 is a video streaming server, connected to a network 306, and capable of streaming video content to any connected client devices.
  • Content server 304 is a download file server, connected to the network 306, and provides file downloads, including video content, to any connected devices.
  • client devices 308, 310 and 312. The client devices can connect to the content servers 302 and 304 over the network 306.
  • the client devices may be a suitably configured PC, set top box, smart TV, tablet or other such device, adapted to request content from the servers 302 and 304.
  • the servers 302 and 304 are arranged as per the server 100 illustrated in Figure 1 .
  • client 308 makes a request for content from server 306.
  • the content is a file download.
  • the request for the content from the client 308 includes an associated delivery deadline for the content.
  • the server 306 thus receives the content request, together with the associated delivery deadline.
  • the method processes content by segments, where a segment is made up of a number of data packets.
  • the file requested is made up of a plurality of segments.
  • the deadline based packet rate calculator 200 in the server 306 calculates a minimum packet dispatch rate for each segment.
  • One approach to calculate the minimum packet dispatch rate is to examine the file size of the content requested, and divide by the time available before the delivery deadline. More complex approaches to determining the minimum dispatch rate can also be used where anticipated levels of congestion are taken into consideration. Further, the delivery deadline could be adjusted to allow for additional data to be buffered at the client to take to allow for expected variability in throughput or delay in the network.
  • step 404 the server starts transmitting the packets of the first segment over the network to the client.
  • the packets are transmitted by the packet dispatcher 204 with a packet dispatch rate at least equal to or greater than the minimum packet dispatch rate.
  • step 406 the server measures the packet loss rate of the network.
  • the packet loss rate is used in step 408 by the QoE max calculator to determine QoE max .
  • QoE max can be determined using the function described earlier by equation (4), which maps packet loss rate onto QoE max .
  • step 410 the QoE of the next segment, which we call QoE predicted , is determined by the predicted QoE assessor 210.
  • QoE predicted will be some finite value dependent on how long the file download is taking so far, and QoE predicted increases with reducing delivery time, as we assume that faster downloads have a higher QoE.
  • step 412 if QoE predicted is less than QoE max , then processing passes to step 414. If QoE predicted is not less than QoE max , then processing passes to step 416.
  • step 414 where QoE predicted is less than QoE max , the server increases the packet dispatch rate of the next segment to be transmitted.
  • step 416 where QoE predicted is not less than QoE max , the packet dispatch rate is decreased, but ensuring that the rate is not less than the minimum packet dispatch rate. So if the minimum packet dispatch rate has been reached, then the packet dispatch rate should not be decreased further.
  • the packets of the next segment are transmitted in step 418 with the new packet dispatch rate from either step 414 or 416.
  • the new packet dispatch rate can be expressed as: dispatch rate ⁇ > dispatch rate + f QoE max ⁇ QoE predicted where f() is a monotonic function.
  • processing can return to step 406, where the packet loss rate is measured, and the packet dispatch rate for the next segment can be adjusted accordingly until all segments are processed.
  • the packet dispatch rate reaches, then exceeds the available bandwidth, the packet loss rate will begin to increase. This will reduce QoE max to the point where it equals the QoE predicted . This will be the stable delivery point, and the packet dispatch rate will no longer change. This is not shown explicitly in Figure 4 , but when the QoE predicted is equal to QoE max , or at least when they are within some tolerance of each other, then the packet dispatch rate is not adjusted. This is the natural stable position reached when this approach is taken.
  • the proposed method replaces the standard TCP congestion response mechanism. Instead, congestion in the network, specifically the packet loss rate experienced, is dealt with using the above described method.
  • a video file encoded at constant bitrate (CBR) is critically sensitive to the delivery bitrate. If the delivery rate is below the media rate, then the QoE is usually completely unacceptable, as the sound will be interrupted and the video will stall. If the file is delivered at above this rate, then there is no increase in QoE.
  • each request would include a delivery deadline which would take into account any buffered video already accumulated in the client.
  • the packet dispatch rate will increase until it exceeds the network capacity, when the packet loss rate will begin to rise. This will cause QoE max to drop accordingly to the point where it equals the actual QoE, or QoE predicted , of the video stream and the system will have reached a stable point.
  • the packet dispatch rate will decrease to ensure that the packet loss rate remains at that consistent with the QoE predicted of the segments of the video stream. This will in turn mean that the throughput reduces.
  • the client will have built up a certain amount of buffer. This means that the delivery deadlines will adjust to allow more time for delivery for subsequent segments.
  • the resulting packet loss rate means that QoE max is less than QoE predicted of the CBR stream. This would mean that, based on QoE max alone, we would not be able to deliver packets at a sufficient rate to stream the video properly.
  • the server will endeavour to dispatch packets at such a rate that the delivery deadline is met, even though this would make QoE predicted of segments in the CBR stream larger than QoE max .
  • variable bit rate or adaptive video streaming session example.
  • a video sequence is encoded at a number of different bit rates, and the system adaptively switches between the different rates in response to network conditions.
  • the packet loss rate determines the TCP throughput, and the system selects the highest bitrate segment whose bitrate is less than or equal to the TCP throughput.
  • the server will monitor the packet loss rate to determine the maximum QoE max . If possible, the server will select segments encoded at a bitrate such that QoE max is not exceeded. The exception is when the (lowest) QoE of the segment encoded with the lowest bitrate is already higher than QoE max , in which case the lowest QoE presentation is selected. The server will schedule delivery of the segment to ensure that the delivery deadline is met.
  • the packet dispatch rate will increase with a corresponding increase in packet loss rate until QoE max reduces to the highest QoE available, just as in the CBR case. This will allow the client to build up a buffer. If subsequently the packet loss rate increases (for example, due to other traffic in the network), then QoE max will be reduced further. The server will select a lower bitrate segment, however the buffer that has been built up means that the server will be given a longer deadline for delivering this segment.
  • Various methods can be used to determine the instantaneous QoE, QoE predicted , for streamed video. Examples include some evaluation of video quality using mean square error (MSE) and peak signal to noise ratio (PSNR), both of which rely on access to the original video as reference. Alternatively, a perceptual quality measure such as PMOS (predicted mean opinion score), could be used instead, as taught in International patent application WO2007/066066 , which takes into account masking effects based on contrast in the picture and does not require a reference video for comparison.
  • MSE mean square error
  • PSNR peak signal to noise ratio
  • PMOS predicted mean opinion score
  • Exemplary embodiments of the invention are realised, at least in part, by executable computer program code which may be embodied in an application program data.
  • executable computer program code When such computer program code is loaded into the memory of the processor 102 in the content server 100, it provides a computer program code structure which is capable of performing at least part of the methods in accordance with the above described exemplary embodiments of the invention.
  • each step of the flow chart can correspond to at least one line of computer program code and that such, in combination with the processor 102 in the content server 100, provides apparatus for effecting the described process.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Environmental & Geological Engineering (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Claims (5)

  1. Verfahren zum Management von Inhalts-Lieferung zwischen einem Server und einem Client über ein Netzwerk, wobei der Inhalt eine Vielzahl von Segmenten umfasst und jedes Segment einen zugeordneten Lieferungs-Termin besitzt, wobei das Verfahren umfasst:
    (i) Ermitteln einer Mindest-Paketübermittlungsrate für die Pakete jedes Segments auf der Basis des jedem Segment zugeordneten Lieferungs-Termins;
    (ii) Übertragen der Pakete eines Segments über das Netzwerk bei einer Paketübermittlungsrate, die mindestens gleich der Mindest-Paketübermittlungsrate ist, und Ermitteln der resultierenden Paketverlustrate in dem Netzwerk;
    (iii) Ermitteln eines Parameters der erfahrungsbasierten Qualität des Netzwerks auf der Basis der ermittelten Paketverlustrate in dem Netzwerk;
    (iv) Ermitteln einer vorhergesagten erfahrungsbasierten Qualität des nächsten zu übertragenden Segments;
    (v) Vergleichen der vorhergesagten erfahrungsbasierten Qualität mit der erfahrungsbasierten Qualität des Netzwerks
    und
    (vi) Einstellen der Paketübermittlungsrate für das nächste Segment in Abhängigkeit von dem Ergebnis des Schrittes des Vergleichens unter Beibehaltung der Paketübermittlungsrate bei der Mindest-Paketübermittlungsrate oder einer höheren Paketübermittlungsrate.
  2. Verfahren nach Anspruch 1, bei dem dann, wenn die vorhergesagte erfahrungsbasierte Qualität kleiner ist als die erfahrungsbasierte Qualität des Netzwerks, die Paketübermittlungsrate für das nächste Segment erhöht wird.
  3. Verfahren nach Anspruch 1 oder Anspruch 2, bei dem dann, wenn die vorhergesagte erfahrungsbasierte Qualität höher ist als die erfahrungsbasierte Qualität des Netzwerks, die Paketübermittlungsrate für das nächste Segment verringert wird.
  4. Verfahren nach einem vorhergehenden Anspruch, bei dem die jedem Segment zugeordneten Lieferungs-Termine dem Server durch den Client bereitgestellt werden.
  5. Server zur Lieferung von Inhalt an einen Client über ein Netzwerk, wobei der Inhalt eine Vielzahl von Segmenten umfasst und jedes Segment einen zugeordneten Lieferungs-Termin besitzt, wobei der Server so ausgebildet ist, dass er
    eine Mindest-Paketübermittlungsrate für die Pakete jedes Segments auf der Basis des jedem Segment zugeordneten Lieferungs-Termins ermittelt;
    die Pakete eines Segments über das Netzwerk bei einer Paketübermittlungsrate, die mindestens gleich der Mindest-Paketübermittlungsrate ist, überträgt und die resultierende Paketverlustrate in dem Netzwerk ermittelt;
    einen Parameter der erfahrungsbasierten Qualität des Netzwerks auf der Basis der ermittelten Paketverlustrate in dem Netzwerk ermittelt;
    eine vorhergesagte erfahrungsbasierte Qualität des nächsten zu übertragenden Segments ermittelt;
    die vorhergesagte erfahrungsbasierte Qualität mit der erfahrungsbasierten Qualität des Netzwerks vergleicht
    und
    die Paketübermittlungsrate für das nächste Segment in Abhängigkeit von dem Ergebnis des Schrittes des Vergleichens unter Beibehaltung der Paketübermittlungsrate bei der Mindest-Paketübermittlungsrate oder einer höheren Paketübermittlungsrate einstellt.
EP14710940.9A 2013-03-27 2014-03-04 Termingebundene inhaltslieferung Active EP2979406B1 (de)

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EP13250037.2A EP2784996A1 (de) 2013-03-27 2013-03-27 Termingebundene Inhaltslieferung
EP14710940.9A EP2979406B1 (de) 2013-03-27 2014-03-04 Termingebundene inhaltslieferung
PCT/GB2014/000078 WO2014155031A1 (en) 2013-03-27 2014-03-04 Deadline driven content delivery

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EP2784996A1 (de) 2014-10-01
EP2979406A1 (de) 2016-02-03
US20160057064A1 (en) 2016-02-25
US10178037B2 (en) 2019-01-08
WO2014155031A1 (en) 2014-10-02

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